Lessons from Inter-Comparison of Decadal Climate Simulations and Observations for the Midwest U.S. and Great Lakes Region
Even with advances in climate modeling, meteorological impact assessment remains elusive, and decision-makers are forced to operate with potentially malinformed predictions. In this article, we investigate the dependence of the Weather Research and Forecasting (WRF) model simulated precipitation and...
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MDPI AG
2019-05-01
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Series: | Atmosphere |
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Online Access: | https://www.mdpi.com/2073-4433/10/5/266 |
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author | Ashish Sharma Alan F. Hamlet Harindra J.S. Fernando |
author_facet | Ashish Sharma Alan F. Hamlet Harindra J.S. Fernando |
author_sort | Ashish Sharma |
collection | DOAJ |
description | Even with advances in climate modeling, meteorological impact assessment remains elusive, and decision-makers are forced to operate with potentially malinformed predictions. In this article, we investigate the dependence of the Weather Research and Forecasting (WRF) model simulated precipitation and temperature at 12- and 4-km horizontal resolutions and compare it with 32-km NARR data and 1/16th-degree gridded observations for the Midwest U.S. and Great Lakes region from 1991 to 2000. We used daily climatology, inter-annual variability, percentile, and dry days as metrics for inter-comparison for precipitation. We also calculated the summer and winter daily seasonal minimum, maximum, and average temperature to delineate the temperature trends. Results showed that NARR data is a useful precipitation product for mean warm season and summer climatological studies, but performs extremely poorly for winter and cold seasons for this region. WRF model simulations at 12- and 4-km horizontal resolutions were able to capture the lake-effect precipitation successfully when driven by observed lake surface temperatures. Simulations at 4-km showed negative bias in capturing precipitation without convective parameterization but captured the number of dry days and 99<sup>th</sup> percentile precipitation extremes well. Overall, our study cautions against hastily pushing for increasingly higher resolution in climate studies, and highlights the need for the careful selection of large-scale boundary forcing data. |
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id | doaj.art-d70c06d4fdd740fca33aaca9bccf15a6 |
institution | Directory Open Access Journal |
issn | 2073-4433 |
language | English |
last_indexed | 2024-04-13T16:47:47Z |
publishDate | 2019-05-01 |
publisher | MDPI AG |
record_format | Article |
series | Atmosphere |
spelling | doaj.art-d70c06d4fdd740fca33aaca9bccf15a62022-12-22T02:39:02ZengMDPI AGAtmosphere2073-44332019-05-0110526610.3390/atmos10050266atmos10050266Lessons from Inter-Comparison of Decadal Climate Simulations and Observations for the Midwest U.S. and Great Lakes RegionAshish Sharma0Alan F. Hamlet1Harindra J.S. Fernando2Climate and Atmospheric Science Section, Illinois State Water Survey, Prairie Research Institute, University of Illinois at Urbana-Champaign, 2204 Griffith Dr., Champaign, IL 61820, USADepartment of Civil & Environmental Engineering and Earth Sciences (CEEES), University of Notre Dame, 156 Fitzpatrick Hall, Notre Dame, IN 46556, USADepartment of Civil & Environmental Engineering and Earth Sciences (CEEES), University of Notre Dame, 156 Fitzpatrick Hall, Notre Dame, IN 46556, USAEven with advances in climate modeling, meteorological impact assessment remains elusive, and decision-makers are forced to operate with potentially malinformed predictions. In this article, we investigate the dependence of the Weather Research and Forecasting (WRF) model simulated precipitation and temperature at 12- and 4-km horizontal resolutions and compare it with 32-km NARR data and 1/16th-degree gridded observations for the Midwest U.S. and Great Lakes region from 1991 to 2000. We used daily climatology, inter-annual variability, percentile, and dry days as metrics for inter-comparison for precipitation. We also calculated the summer and winter daily seasonal minimum, maximum, and average temperature to delineate the temperature trends. Results showed that NARR data is a useful precipitation product for mean warm season and summer climatological studies, but performs extremely poorly for winter and cold seasons for this region. WRF model simulations at 12- and 4-km horizontal resolutions were able to capture the lake-effect precipitation successfully when driven by observed lake surface temperatures. Simulations at 4-km showed negative bias in capturing precipitation without convective parameterization but captured the number of dry days and 99<sup>th</sup> percentile precipitation extremes well. Overall, our study cautions against hastily pushing for increasingly higher resolution in climate studies, and highlights the need for the careful selection of large-scale boundary forcing data.https://www.mdpi.com/2073-4433/10/5/266regional climate modelingclimatologyclimate extremesWRF modeltemperatureprecipitation |
spellingShingle | Ashish Sharma Alan F. Hamlet Harindra J.S. Fernando Lessons from Inter-Comparison of Decadal Climate Simulations and Observations for the Midwest U.S. and Great Lakes Region Atmosphere regional climate modeling climatology climate extremes WRF model temperature precipitation |
title | Lessons from Inter-Comparison of Decadal Climate Simulations and Observations for the Midwest U.S. and Great Lakes Region |
title_full | Lessons from Inter-Comparison of Decadal Climate Simulations and Observations for the Midwest U.S. and Great Lakes Region |
title_fullStr | Lessons from Inter-Comparison of Decadal Climate Simulations and Observations for the Midwest U.S. and Great Lakes Region |
title_full_unstemmed | Lessons from Inter-Comparison of Decadal Climate Simulations and Observations for the Midwest U.S. and Great Lakes Region |
title_short | Lessons from Inter-Comparison of Decadal Climate Simulations and Observations for the Midwest U.S. and Great Lakes Region |
title_sort | lessons from inter comparison of decadal climate simulations and observations for the midwest u s and great lakes region |
topic | regional climate modeling climatology climate extremes WRF model temperature precipitation |
url | https://www.mdpi.com/2073-4433/10/5/266 |
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